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Conference Paper: An audit environment for outsourcing of frequent itemset mining

TitleAn audit environment for outsourcing of frequent itemset mining
Authors
Issue Date2009
PublisherACM.
Citation
The 35th International Conference on Very Large Data Bases (VLDB 2009), Lyon, France, 24-28 August 2009. In Proceedings of the VLDB Endowment, 2009, v. 2 n. 1, p. 1162-1173 How to Cite?
AbstractFinding frequent itemsets is the most costly task in association rule mining. Outsourcing this task to a service provider brings several benefits to the data owner such as cost relief and a less commitment to storage and computational resources. Mining results, however, can be corrupted if the service provider (i) is honest but makes mistakes in the mining process, or (ii) is lazy and reduces costly computation, returning incomplete results, or (iii) is malicious and contaminates the mining results. We address the integrity issue in the outsourcing process, i.e., how the data owner verifies the correctness of the mining results. For this purpose, we propose and develop an audit environment, which consists of a database transformation method and a result verification method. The main component of our audit environment is an artificial itemset planting (AIP) technique. We provide a theoretical foundation on our technique by proving its appropriateness and showing probabilistic guarantees about the correctness of the verification process. Through analytical and experimental studies, we show that our technique is both effective and efficient. Copyright 2009 VLDB
Persistent Identifierhttp://hdl.handle.net/10722/93381
ISSN

 

DC FieldValueLanguage
dc.contributor.authorWong, WKen_HK
dc.contributor.authorCheung, DWLen_HK
dc.contributor.authorHung, Een_HK
dc.contributor.authorKao, Ben_HK
dc.contributor.authorMamoulis, Nen_HK
dc.date.accessioned2010-09-25T14:59:22Z-
dc.date.available2010-09-25T14:59:22Z-
dc.date.issued2009en_HK
dc.identifier.citationThe 35th International Conference on Very Large Data Bases (VLDB 2009), Lyon, France, 24-28 August 2009. In Proceedings of the VLDB Endowment, 2009, v. 2 n. 1, p. 1162-1173-
dc.identifier.issn2150-8097-
dc.identifier.urihttp://hdl.handle.net/10722/93381-
dc.description.abstractFinding frequent itemsets is the most costly task in association rule mining. Outsourcing this task to a service provider brings several benefits to the data owner such as cost relief and a less commitment to storage and computational resources. Mining results, however, can be corrupted if the service provider (i) is honest but makes mistakes in the mining process, or (ii) is lazy and reduces costly computation, returning incomplete results, or (iii) is malicious and contaminates the mining results. We address the integrity issue in the outsourcing process, i.e., how the data owner verifies the correctness of the mining results. For this purpose, we propose and develop an audit environment, which consists of a database transformation method and a result verification method. The main component of our audit environment is an artificial itemset planting (AIP) technique. We provide a theoretical foundation on our technique by proving its appropriateness and showing probabilistic guarantees about the correctness of the verification process. Through analytical and experimental studies, we show that our technique is both effective and efficient. Copyright 2009 VLDB-
dc.languageengen_HK
dc.publisherACM.-
dc.relation.ispartofProceedings of the VLDB Endowmenten_HK
dc.titleAn audit environment for outsourcing of frequent itemset miningen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=2150-8097 &volume=2&issue=1&spage=1162&epage=1173&date=2009&atitle=An+audit+environment+for+outsourcing+of+frequent+itemset+mining-
dc.identifier.emailWong, WK: wkwong2@cs.hku.hken_HK
dc.identifier.emailCheung, DWL: dcheung@cs.hku.hken_HK
dc.identifier.emailHung, E: csehung@comp.polyu.edu.hken_HK
dc.identifier.emailKao, B: kao@cs.hku.hk-
dc.identifier.emailMamoulis, N: nikos@cs.hku.hk-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.hkuros161668en_HK
dc.identifier.volume2-
dc.identifier.issue1-
dc.identifier.spage1162-
dc.identifier.epage1173-
dc.description.otherThe 35th International Conference on Very Large Data Bases (VLDB 2009), Lyon, France, 24-28 August 2009. In Proceedings of the VLDB Endowment, 2009, v. 2 n. 1, p. 1162-1173-

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